Apache Drill vs. Apache HBase

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Drill
Score 8.1 out of 10
N/A
Apache Drill is a schema-free query engine for use with NoSQL or Hadoop data or file storage systems and databases.N/A
HBase
Score 7.3 out of 10
N/A
The Apache HBase project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable.N/A
Pricing
Apache DrillApache HBase
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache DrillHBase
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache DrillApache HBase
Considered Both Products
Apache Drill
Chose Apache Drill
compared to presto, has more support than prestodb.
Impala has limitations to what drill can support
apache phoenix only supports for hbase. no support for cassandra.
HBase
Top Pros
Top Cons
Features
Apache DrillApache HBase
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache Drill
-
Ratings
Apache HBase
7.7
5 Ratings
13% below category average
Performance00 Ratings7.15 Ratings
Availability00 Ratings7.85 Ratings
Concurrency00 Ratings7.05 Ratings
Security00 Ratings7.85 Ratings
Scalability00 Ratings8.65 Ratings
Data model flexibility00 Ratings7.15 Ratings
Deployment model flexibility00 Ratings8.25 Ratings
Best Alternatives
Apache DrillApache HBase
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.8 out of 10
IBM Cloudant
IBM Cloudant
Score 7.8 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.8 out of 10
IBM Cloudant
IBM Cloudant
Score 7.8 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.8 out of 10
IBM Cloudant
IBM Cloudant
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache DrillApache HBase
Likelihood to Recommend
8.0
(1 ratings)
7.7
(10 ratings)
Likelihood to Renew
7.0
(1 ratings)
7.9
(10 ratings)
User Testimonials
Apache DrillApache HBase
Likelihood to Recommend
Apache
if you're doing joins from hBASE, hdfs, cassandra and redis, then this works. Using it as a be all end all does not suit it. This is not your straight forward magic software that works for all scenarios. One needs to determine the use case to see if Apache Drill fits the needs. 3/4 of the time, usually it does.
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Apache
Hbase is well suited for large organizations with millions of operations performing on tables, real-time lookup of records in a table, range queries, random reads and writes and online analytics operations. Hbase cannot be replaced for traditional databases as it cannot support all the features, CPU and memory intensive. Observed increased latency when using with MapReduce job joins.
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Pros
Apache
  • queries multiple data sources with ease.
  • supports sql, so non technical users who know sql, can run query sets
  • 3rd party tools, like tableau, zoom data and looker were able to connect with no issues
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Apache
  • Scalability. HBase can scale to trillions of records.
  • Fast. HBase is extremely fast to scan values or retrieve individual records by key.
  • HBase can be accessed by standard SQL via Apache Phoenix.
  • Integrated. I can easily store and retrieve data from HBase using Apache Spark.
  • It is easy to set up DR and backups.
  • Ingest. It is easy to ingest data into HBase via shell, Java, Apache NiFi, Storm, Spark, Flink, Python and other means.
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Cons
Apache
  • deployment. Not as easy
  • configuration isn't as straight forward, especially with the documentation
  • Garbage collection could be improved upon
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Apache
  • There are very few commands in HBase.
  • Stored procedures functionality is not available so it should be implemented.
  • HBase is CPU and Memory intensive with large sequential input or output access while as Map Reduce jobs are primarily input or output bound with fixed memory. HBase integrated with Map-reduce jobs will result in random latencies.
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Likelihood to Renew
Apache
if Presto comes up with more support (ie hbase, s3), then its strongly possible that we'll move from apache drill to prestoDB. However, Apache drill needs more configuration ease, especially when it comes to garbage collection tuning. If apache drill could support also sparkSQL and Flume, then it does change drill into being something more valuable than prestoDB
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Apache
There's really not anything else out there that I've seen comparable for my use cases. HBase has never proven me wrong. Some companies align their whole business on HBase and are moving all of their infrastructure from other database engines to HBase. It's also open source and has a very collaborative community.
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Alternatives Considered
Apache
compared to presto, has more support than prestodb. Impala has limitations to what drill can support apache phoenix only supports for hbase. no support for cassandra. Apache drill was chosen, because of the multiple data stores that it supports htat the other 3 do not support. Presto does not support hbase as of yet. Impala does not support query to cassandra
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Apache
Cassandra os great for writes. But with large datasets, depending, not as great as HBASE. Cassandra does support parquet now. HBase still performance issues. Cassandra has use cases of being used as time series. HBase, it fails miserably. GeoSpatial data, Hbase does work to an extent. HA between the two are almost the same.
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Return on Investment
Apache
  • Configuration has taken some serious time out.
  • Garbage collection tuning. is a constant hassle. time and effort applied to it, vs dedicating resources elsewhere.
  • w/ sql support, reduces the need of devs to generate the resultset for analysts, when they can run queries themselves (if they know sql).
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Apache
  • As Hbase is a noSql database, here we don't have transaction support and we cannot do many operations on the data.
  • Not having the feature of primary or a composite primary key is an issue as the architecture to be defined cannot be the same legacy type. Also the transaction concept is not applicable here.
  • The way data is printed on console is not so user-friendly. So we had to use some abstraction over HBase (eg apache phoenix) which means there is one new component to handle.
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